The USERN organization (Universal Scientific Education and Research Network) will soon issue its next bulletin, to which I contribute with an opening message in the function of the president of the organization. I thought the contents of the message would be of some interest to some of my readers here, so I decided to attach below my original text. Before we go there, though, I would invite all of you to learn about USERN by visiting its web site, and consider becoming a member (it is free!) - or even better, if you share our views, support us!

A message from the USERN President

A revolution is taking place, but we seem to not yet realize it. 
Paradigm shifting technologies often produce an abrupt transition when they get adopted. However, that transition is not easy to recognize early on: the effects of an exponential trend appear linear at the begninning, so the explosive force of the transition that occurs a little later takes many by surprise.

Today I am traveling to Banff, a pleasant mountain resort in western Canada, to attend a workshop on systematic uncertainties. Yes, you heard that right - a bunch of physicists and statisticians will be gathering in a secluded location for a whole week, with the sole purpose of debating on that exotic topic. How weird is that? I bet most of you don't think much of systematic uncertainties. What are they, anyway?

Known unknowns

The Swedish Institute for Space Physics (IRF) is located in Kiruna, a minerary town close to the northern tip of Sweden, above the arctic polar circle. The Space Campus of Kiruna is one of three different centres - the IRF space lab, the EISCAT center, and the Lulea University of Technology department of Space Technology and Atmospheric Science. Close to the complex is the Esrange space center, a multipurpose launching base benefiting from a large unpopulated impact and recovery area.



Above: the IRF from the visitor parking

In the last couple of days I have been busy writing a project to explore the potential of artificial intelligence to extract more information from particle detectors. In fact, while the development of these instruments in the course of the past 80 years has closely followed, and sometimes been a driver, of technological developments, I can see the issue of a progressive mis-alignment of detector design with the ultimate potential and final goals of large experiments. That mis-alignment is due to the rapid evolution of deep learning tools. They have now become the real elephant in the room in this area of studies: an entity that is present, but that risks being ignored despite its enormous impact.